A whole-brain single-cell atlas of circadian neural activity in mice

Researchers mapped spontaneous neural activity across the entire mouse brain throughout the circadian cycle, asking how brain regions coordinate their activity rhythms over time. They collected 144 mouse brains over two days under constant darkness, then used tissue clearing and whole-brain c-Fos immunostaining — a marker of neural activity — to quantify activity at single-cell resolution across hundreds of anatomically defined areas. Nearly 80% of the 642 regions examined showed circadian oscillations, but crucially, these oscillations peaked at different phases, suggesting that timing differences reflect functional specialization rather than uniform brain-wide synchrony. Finer voxel-level analysis revealed additional complexity within individual regions. The team also showed that c-Fos activity patterns across the brain could accurately predict circadian time using omics-based computational methods. This atlas offers a detailed resource for understanding how the brain's internal clock shapes neural coordination and for accounting for time-of-day effects in neuroscience and pharmacology research.

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The functional landscape of coding variation in the familial hypercholesterolemia gene <i>LDLR</i>

Researchers created a near-comprehensive map of how coding variants in LDLR—the gene most strongly linked to familial hypercholesterolemia and cardiovascular disease risk—affect protein function. Using high-throughput assays, they measured the consequences of roughly 17,000 variants on two key outcomes: LDLR abundance at the cell surface and the ability of cells to take up LDL cholesterol. The resulting sequence-function maps aligned well with established LDLR biology while also revealing new functional insights. Critically, about half of LDLR missense variants encountered in clinical practice currently lack definitive classifications; the functional scores generated here correlated with hyperlipidemia phenotypes observed in prospective patient cohorts and improved genetic risk prediction when combined with polygenic scores. This resource has the potential to resolve long-standing variant classification gaps, accelerate familial hypercholesterolemia diagnosis, and ultimately guide earlier, more targeted interventions for patients at elevated cardiovascular risk.

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The oncogenome of the domestic cat

Researchers mapped the mutational landscape of cancer in domestic cats by performing targeted sequencing of nearly 500 tumor-normal tissue pairs spanning 13 tumor types, focusing on feline counterparts of roughly 1,000 known human cancer genes. TP53 emerged as the most frequently mutated gene, while the most common copy number changes involved loss of PTEN or FAS and gain of MYC. The study identified 31 cancer driver genes, characteristic mutational signatures, viral sequences, and germline variants that predispose cats to tumors. The feline oncogenome showed substantial overlap with its human equivalent, reinforcing the cat's utility as a comparative cancer model. The work also flagged potentially actionable mutations, supporting a "One Medicine" framework in which insights from veterinary oncology can inform human cancer research and vice versa.

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